Technical Field
The embodiments herein generally relate to classification systems, and, more particularly, to a computer implemented classification system and method for classifying one or more users.
Description of the Related Art
Technology has developed exponentially with usage of electronics and computer systems. With the development of technology, the quantity of data has significantly grown. With the increasing amount of data processing, it has been difficult to analyze and classify such large data sets. Efficient computation, and analyses of the large data sets are increasingly prevalent in recent years. A key to achieve this is by executing parallel algorithms and classify them or one or more users associated with the data sets to meet the performance requirements in such a large data set analyses. Data mining is a process of identifying new patterns from the large data sets involving, database systems, statistics, and machine learning.
Support Vector Machines (SVMs) are supervised machine learning models used for classification and regression purpose. Theoretically they are one of the best known linear classifiers. However, (a) all problems are not linearly separable, hence a suitable Kernel has to be chosen (or selected) to map the classification problem or to be used in support vector machine classification to a linearly separable feature space, and (b) the training time required for SVM grows dramatically with the size of the training data set. Accordingly, there remains a need for a classification system and method to analyse the data set and classify one or more users corresponding to the data sets.